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learning objectives work best for sparse, high-dimensional and heterogeneous microbiome data, and turn the selected approaches into robust trainable models. Your work will cover both foundation-model
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objectives work best for sparse, high-dimensional and heterogeneous microbiome data, and turn the selected approaches into robust trainable models. Your work will cover both foundation-model pretraining and
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on text and image feature learning for news ecosystems, analysing the complex multidimensional feature space of visual information to support data-driven journalism. This includes experiments
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back-end development strong communication and academic writing skills; Good to have criteria: experience working with geospatial or image-based data; an interest in urban health, mobility, public space
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and authorities interested in improving civic participation. The research in this postdoctoral position focuses on text and image feature learning for news ecosystems, analysing the complex